For a typical method of visualizing statistical data, there is a representation method of region segmentation type such as a column chart or a pie graph. It is a method of visualizing contents of the statistical data by classifying the statistical data to represent them with class values meaning the contents of the data and section values meaning an order of the data, and segmenting a drawing such as a rectangle (in the case of the column chart) or a circle (in the case of the pie graph) into small regions of sizes corresponding to the class values.
When the statistical data is classified, there is the case where the number of classes becomes very large or the case where the class values become very small. When these cases are represented in a simple band or pie graph, in which the respective small regions are only lined up in a sequence, the small regions corresponding to the small class values are collapsed thinly so as to become difficult to read. In addition, if the number of the classes is large, many borders of the respective small regions are arranged at small intervals so that the graph becomes difficult to read.
FIG. 12 shows an example of the column chart. Referring to FIG. 12, parts having the small class values are collapsed thinly to become difficult to read.
For a solution for solving such problems, a visualization method is known of representing the class values of the statistical data by two-dimensional region segmentation. A typical one such method is Treemap method. FIG. 13 shows examples of drawing in the Treemap method in which FIG. 13(A) is an example of drawing the statistical data including two hierarchies, and FIG. 13(B) is an example of drawing the statistical data including three hierarchies.
In the Treemap method, the hierarchies are represented in the region segmentation such as a nested column chart by a repeat process, such that first a rectangular region forming the graph is segmented vertically, next the respective regions are segmented horizontally (see FIG. 13(A)), and if necessary, the respective regions are further segmented vertically (see FIG. 13(B)). The Treemap method is described in detail in: Johnson B., et al., Tree-Maps: A Space Filling Approach to the Visualization of Hierarchical Information Space, IEEE Visualization '91, pp. 275-282, 1991.
Furthermore, based on the Treemap method, there are representation methods such as the Squarified Treemap method or the Clustered Treemap method, in which two-dimensional region segmentation is performed with respect to the statistical data without a hierarchical structure, and the rectangular region is segmented into a group of rectangles having areas proportional to the class values. FIG. 14 shows an example of a drawing in the Squarified Treemap method, and FIG. 15 shows an example of a drawing in the Clustered Treemap method.
In these methods, the classified statistical data are sorted based on the class values, and the rectangles having the sizes corresponding to the respective class values (small regions), are arranged within the rectangular region corresponding to the entire statistical data in a descending order of the class values. In addition, the entire rectangular region is segmented into the group of the rectangles in shapes as near square as possible (that is, differences between longer sides and shorter sides of the rectangles are as small as possible). These methods, in which the rectangles corresponding to the class values are represented in the near square shapes, are characterized in that:                the rectangles corresponding to the small class values are prevented from being collapsed to become invisible; and        the sizes of the rectangles (class values) are easy to compare because the shapes of the rectangles are nearly similar.        
In addition, in the Ordered Treemap method developed similarly based on the Treemap method, the rectangles corresponding to the class values are arranged in an order of the section values such that the rectangles become near square shapes. FIG. 16 shows an example of drawing in the Ordered Treemap method. This method is characterized in that adjacent class values are easy to compare visually because positional relation of the rectangles is the order of the section values of the classes.
As described above, though some methods have been proposed as methods of visualizing classified statistical data, there have been drawbacks as follows in these methods. In the Squarified Treemap method or the Clustered Treemap method, rectangles corresponding to class values are arranged based on sizes of the class values so that positional relation of the arranged rectangles becomes independent of section values. Therefore, it has been difficult to visually compare the data adjacent in the section values.
In addition, in the Ordered Treemap method, the rectangles corresponding to the class values are arranged in an order of the section values, so that it is easier than the above described two methods to visually compare the data adjacent in the section values. However, since it has not been considered to arrange the adjacent section values to be adjacent to each other on a screen, the rectangles corresponding to the data having the adjacent section values are arranged at separate positions on the screen, thereby easiness of the data comparison may be degraded.
Furthermore, in the Ordered Treemap method, since arranging the rectangles in the order of the section values is prioritized, shapes of the rectangles often do not become near square (that is, differences between longer sides and shorter sides of the rectangles often do not become small), in comparison with the above described two methods of prioritizing the sizes of the class values, thereby the comparison in the class values may be difficult.
Also the Treemap method, in which, with respect to the statistical data having a hierarchical structure, a nested column chart is configured with the above described hierarchical structure reflected therein, has had drawbacks that a simple column chart is configured if the statistical data without the hierarchical structure is visualized, that the rectangles corresponding to the data having the adjacent section values are arranged at the separate positions on the screen, thereby the easiness of the data comparison may be degraded similarly as the Ordered Treemap method, that an operation for shaping the arranged rectangles to be near squares is not performed, thereby the comparison in the class values may be difficult, and the like.